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#!/usr/bin/env python3 | ||
# | ||
# Authors: Christoph Lehner 2024 | ||
# | ||
# Benchmark Indexed Sum | ||
# | ||
import gpt as g | ||
import numpy as np | ||
import cgpt | ||
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# mute random number generation | ||
g.default.set_verbose("random", False) | ||
rng = g.random("benchmark") | ||
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# main test loop | ||
for precision in [g.single, g.double]: | ||
grid = g.grid(g.default.get_ivec("--grid", [16, 16, 16, 32], 4), precision) | ||
N = 100 | ||
Nwarmup = 5 | ||
g.message( | ||
f""" | ||
Indexed Sum Benchmark with | ||
fdimensions : {grid.fdimensions} | ||
precision : {precision.__name__} | ||
""" | ||
) | ||
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# coordinates | ||
idx = g.complex(grid) | ||
idx[:] = np.ascontiguousarray(g.coordinates(idx)[:, 3].astype(np.complex128)) | ||
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# Source and destination | ||
for tp in [g.ot_singlet(), g.ot_vector_spin_color(4, 3), g.ot_matrix_spin_color(4, 3)]: | ||
for n in [1, 4, 16]: | ||
one = [g.lattice(grid, tp) for i in range(n)] | ||
rng.cnormal(one) | ||
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# Rank inner product | ||
nbytes = (one[0].global_bytes() * n + idx.global_bytes()) * N | ||
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# Time global | ||
dt = 0.0 | ||
cgpt.timer_begin() | ||
for it in range(N + Nwarmup): | ||
if it >= Nwarmup: | ||
dt -= g.time() | ||
ip = g.indexed_sum(one, idx, grid.gdimensions[3]) | ||
if it >= Nwarmup: | ||
dt += g.time() | ||
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# Time local | ||
rank_dt = 0.0 | ||
for it in range(N + Nwarmup): | ||
if it >= Nwarmup: | ||
rank_dt -= g.time() | ||
g.slice(one, 3) | ||
if it >= Nwarmup: | ||
rank_dt += g.time() | ||
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# Report | ||
GBPerSec = nbytes / dt / 1e9 | ||
rank_GBPerSec = nbytes / rank_dt / 1e9 | ||
cgpt_t = g.timer("ris") | ||
cgpt_t += cgpt.timer_end() | ||
g.message( | ||
f"""{N} indexed_sum | ||
Object type : {tp.__name__} | ||
Block : {n} | ||
Time to complete : {dt:.2f} s (indexed_sum) | ||
Time to complete : {rank_dt:.2f} s (slice) | ||
Effective memory bandwidth : {GBPerSec:.2f} GB/s (indexed_sum) | ||
Effective memory bandwidth : {rank_GBPerSec:.2f} GB/s (slice) | ||
{cgpt_t} | ||
""" | ||
) | ||
|
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